"3D modeling tutorial for creating a table tennis bat in Blender" matching MCP servers:

Enables AI assistants to clean PDB structures and run initial-stage energy relaxation for biomolecular modeling. It provides a structured workflow for preparing structures before production molecular dynamics or coarse-graining pipelines.

Enables genomic sequence analysis through the Evo 2 model, supporting DNA sequence scoring, embedding, generation, and variant effect prediction with multiple model checkpoints (7B, 40B, 1B parameters).

Enables variant annotation and effect prediction using the Ensembl VEP API, with support for batch and single queries.

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

Connects 3D Slicer with AI assistants through the Model Context Protocol, enabling medical image processing and scene manipulation using natural language.

Enables AI agents to conversationally interact with genomics research networks for data analysis and discovery across multiple Omics AI Explorer platforms. It provides tools for exploring data collections, examining table schemas, and executing SQL queries against datasets like Viral AI and Neuroscience AI.

A Model Context Protocol (MCP) server that provides access to the Protein Data Bank (PDB) - the worldwide repository of information about the 3D structures of proteins, nucleic acids, and complex assemblies.

A Model Context Protocol server providing programmatic access to 3D protein structural data from RCSB PDB, PDBe, and UniProt, enabling search, retrieval, comparison, and analysis of protein structures.

Searches UniProt by protein name to find accession numbers and retrieves detailed protein structure information from AlphaFold, including direct links to 3D structural predictions.

Provides access to AlphaFold predicted protein 3D structures from EBI, enabling retrieval of prediction metadata, summaries, annotations, and UniProt data.

Integrates GROMACS molecular dynamics simulations with VMD visualization, enabling setup, execution, analysis, and 3D visualization of molecular dynamics workflows through natural language.

Enables LLM agents to perform stateful genome-scale metabolic modeling with COBRApy through the Model Context Protocol, including loading models, knocking out genes, running flux balance analysis, and inspecting flux distributions.

Enables LLMs and AI agents to query a biomedical knowledge graph stored in RedisGraph, with tools for concept search, synonym enrichment, and study variable discovery through semantic relationships.

Enables protein modeling and design using the Rosetta suite via Docker, including structure refinement, mutation stability analysis, docking, and loop modeling through natural language commands.

Enables in-chat scientific viewers for molecular structures, sequence alignments, and slide images, plus data tools for searching structures, fetching sequences, aligning them, and drafting NGS analysis plans.

An MCP server that grounds protein research in the UniProt SPARQL endpoint, providing tools for querying proteins, sequences, variants, diseases, and more via intent-named tools and raw SPARQL.

Enables language models to search biomedical literature, fetch sequences, and follow links across Entrez databases through eleven read-only tools wrapping the nine NCBI Entrez E-utilities. It handles URL building, pacing, redirects, response caps, and API-key redaction so queries can be answered without a browser or scraping.

Grounds gene-nomenclature work in the HUGO Gene Nomenclature Committee (HGNC) dataset, enabling resolution of gene symbols and IDs to canonical HGNC identifiers, plus cross-references and batch operations.

MCP server that provides tools to query harmonized gene-disease validity data from the Gene Curation Coalition, supporting consensus and conflict detection for gene-disease assertions.

MCP server exposing REINVENT4 generative molecular-design operations as validated, LLM-callable tools for drug discovery, including sampling, transfer learning, reinforcement learning, and molecular analysis.